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Neural Basis of Haptic Object Processing, The

Canadian Journal of Experimental Psychology, Sep 2007 by James, Thomas W, Kim, Sunah, Fisher, Jerry S

Abstract

We review the organization of the neural networks that underlie haptic object processing and compare that organization with the visual system. Haptic object processing is separated into at least two neural pathways, one for geometric properties or shape, and one for material properties, including texture. Like vision, haptic processing pathways are organized into a hierarchy of processing stages, with different stages represented by different brain areas. In addition, the haptic pathway for shape processing may be further subdivided into different streams for action and perception. These streams may be analogous to the action and perception streams of the visual system and represent two points of neural convergence for vision and haptics.

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Résumé Nous examinons l'organisation des réseaux neuronaux qui sous-tendent le traitement haptique des objets et comparons cette structure au système visuel. Le traitement haptique des objets est séparé en au moins deux circuits neuronaux : un pour les propriétés géométriques ou formes, et l'autre pour les propriétés physiques, dont la texture. Comme dans le cas de la vision, les circuits de traitement haptique sont organisés en une hiérarchie de stades de traitement, les différents stades étant représentés par des aires différentes du cerveau. De plus, le circuit haptique impliqué dans le traitement des formes peut être encore subdivisé en différentes voies pour l'analyse et la perception. Ces voies peuvent être analogues aux voies d'action et de perception du système visuel, et représentent deux points de convergence neuronale pour les modalités visuelle et haptique.

Object recognition is a fundamental cognitive operation performed countless times each day. Yet despite decades of research into the mechanisms of human object recognition, we have only the barest idea of how this complex problem is solved so efficiently by the brain. Routine object recognition seems effortless and automatic to us, yet attempts to create artificial systems that recognize objects in the way that humans do have had little practical success. One suggestion for the slow progress of artificial recognition systems is the reliance of those systems on purely visual input, even though objects in our environment are a source of incredibly rich multisensory stimulation. For instance, a glass containing a soft drink can produce sensations of taste and smell, but you can also see the glass, watch the bubbles move, reach out and feel the bubbles burst against your skin and even hear them fizz.

It is not a stretch to suggest that objects such as the soft drink are the rule, as opposed to the exception, in our world. It seems equally likely that when we are attempting to ascertain the identity of an object in our environment, we use all the information available, regardless of the sensory modality. However, despite the multisensory nature of real-world object recognition, until recently object recognition was almost exclusively studied using unisensory stimuli. Furthermore, the majority of those unisensory experiments used visual stimuli. Recently, though, there has been a surge of interest in multisensory phenomena, including multisensory object recognition (Calvert, Spence, & Stein, 2004). Because relatively less is known about how object recognition occurs using sensory inputs besides vision, the increased interest in multisensory recognition has led to increased interest in nonvisual unisensory object recognition.

Of the various candidate sensory systems besides vision by which objects can be recognized, perhaps the most actively studied has been touch. Here, we will distinguish between passive touch and haptics, which we define as active use of the hands to retrieve the attributes of an object stimulus, using both cutaneous and kinesthetic inputs. Haptic object recognition has been studied behaviourally and in patients with brain damage for many decades. It has been studied using neurophysiologic and neuroimaging techniques since their inception. The intent of this chapter is to present an overview of the neural mechanisms of haptic object recognition. We will focus particularly on mechanisms involving the object attributes of shape and surface texture.

Neural Mechanisms of Shape Recognition

One self-imposed limitation on the breadth of object recognition research has been an emphasis on analyzing the geometric characteristics of objects (e.g., size or shape). Like the preferential study of vision over other sensory systems, there are some potentially acceptable reasons for the bias toward the study of shape over other object characteristics. First, shape information by itself is sufficient for highly efficient object recognition (Biederman, 1987); it does not need to be combined with other object characteristics. Second, one of the strongest indicators of category membership for an object is the configuration of its parts or features, that is, its geometric or spatial properties (Rosch, Mervis, Gray, Johnson, & Boyes-Braem, 1976). As it turns out, vision is better suited to retrieving an object's shape than any other sensory system; this perhaps explains the predominance of visual shape studies in the object recognition literature. But, haptics can also extract useful shape information from objects and use it for the purposes of recognition (Klatzky, Lederman, & Reed, 1987), particularly for recognition at the basic level of categorization (Lederman & Klatzky, 1990).

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Neural Basis of Haptic Object Processing, The

Canadian Journal of Experimental Psychology, Sep 2007 by James, Thomas W, Kim, Sunah, Fisher, Jerry S

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